System Dynamics and Innovation
in Food Networks
2014
Proceedings of the 8thInternational European Forum on System Dynamics and Innovation in
Food Networks, organized by the International Center for Food Chain and Network
Research, University of Bonn, Germany
February 17-21, 2014, Innsbruck-Igls, Austria
officially endorsed by
EAAE(European Association of Agricultural Economists)
IFAMA (International Food and Agribusiness Management Assoc.)
AIEA2 (Assoc. Intern. di Economia Alimentare e Agro-Industriale)
CIGR (Intern. Commission of Agric. and Biosystems Engineering)
INFITA (Intern. Network for IT in Agric., Food and the Environment)
edited by
U. Rickert and G. Schiefer
2014, Universität Bonn-ILB, Germany,
ISSN 2194-511X
Gaetano Martino and Miroslava Bavorovà
An Analysis of Food Safety Private Investments Drivers in the Italian
Meat Sector
Gaetano Martino1 and Miroslava Bavorovà2
1
University of Perugia, Italy
2
Martin Luther University, Halle, Germany
gaetano.martino@unipg.it; miroslava.bavorova@landw.uni-halle.de,
1
Introduction
The general focus of this study is to investigate the decision to invest in food safety as a field of
connection between public and private strategies. The objective if the study is to investigate how the
legislation pressure influence the decision to invest in food safety systems. The basic idea is to
conceptualize the allocation of the decision right to invest among the transaction party, counterparty
and regulator as a source of drivers of investments. While the allocation of the decision rights is
recognized as the key factor in coping with uncertainty (Gibbons, 2005), it is also here held as term of
the micro-foundations of the organizational arrangements (Grandori, Furnari, 2008).
Food companies and agricultural farms pay a great and necessary attention to technologies and
economic relationships and arrangements aimed at enhancing and ensuring the due degree of products
safety. In all the chain stages, adequate technologies are needed in order to carry out the productive
process according to the best prerequisites identified by health and food sciences. Policy interventions
intended to prevent food safety crisis have shaped the institutional environment of food systems
channelling the companies strategies and have induced, with the technological requirements, the raise
of complex organizational forms (Hobbs, 2002; Mènard and Valceschini, 2005). The food chain actors
elaborate complex strategies in which technological and organizational choices and institutional
commitments assure the food safety level demanded by public and private safety regulations and
strategies.
Although the process depicted has been widely investigated under economic and organizational views, a
lack of knowledge still remains about the determinants of the investment in food safety strategic
choices. There are several drivers of food safety oriented investments.
In the empirical investigation we consider the influence of the law and economic drivers
separately for the following food safety risks management systems: HACCP, certification, geographical
indications and brand. The knowledge of such an influence provides a better comprehension of the
micro-level motivations of food safety strategies adopted and help to understand specific characteristics
of the Agri-food governance modes and could favour the elaboration of policy intervention.
The paper is organized as follows: in the second section we introduce the analytical framework. The
data analysis approach and the empirical results are presented and discussed in the sections three. The
last paragraph is dedicated to conclusions.
229
Gaetano Martino and Miroslava Bavorovà
2
Analytical framework
2.1 Coordination and information issues and uncertainty
The choice of the efficient governance structure allows the agents to carry out the planned transaction
(Williamson, 1985, 1991). Namely the transaction parties seek to align the attributes of the transaction –
asset specificity, uncertainty and frequency – to the characteristics of the governance structure
(Williamson, 1991, Masten, 2000; Mènard, 2005). Normally, quality and safety strategies in Agri-Food
Chains require to make highly specific investments and to deal with uncertainty. Uncertainty
exacerbates the effect of asset specificity in choosing more centralized governance structure
(Williamson, 1991) and determine the necessity to adapt the governance mode (Mènard, 2004) to
unforeseen contingencies (Williamson, 1991, Gibbons, 2005; Gibbon et al., 2013). As a consequence
hybrid governance modes became largely diffused (Mènard, Valceschini, 2005; Martino, Perugini, 2005).
Coordination issues influence the safety performance of the food systems. The safety level of food
products supplied depends on the behaviour of all agents involved in the food chain. This is because the
source of accidents - chemical, physical, microbiological, etc. - may occur at any stage of the system and
because remedies and precautions intentionally implemented may fail due to technological flaws or
human errors. Thus the safe foods provision involves the choice of appropriate forms of governance
able to guarantee the expected objectives. The safety level is an outcome of the coordination designed
by the chain agents (Martino, Perugini, 2006; Lupien, 2005; Charlier, Valceschini, 2008; Hammoudi et al.,
2009).
The most of the safety characteristics are credence in nature (Hobbs, 2002) therefore an unavoidable
information asymmetry arises among the chains partners. The market failure determined by the
information asymmetry is an important cause of public intervention (Unnehever, Jensen, 1999). Public
intervention takes different forms characterized by various specific objectives and intensity (GarciaMartinez et al., 2007; Henson, Holt, 2000). Likewise, the information asymmetry is a further important
issue to be taken into consideration. Furthermore the unequal distribution of information about food
products characteristics requires the agents to design and to implement mechanisms to gather and to
channel information and to carry out dedicated activities.
Coordination and information issues motivate the critical importance of the organization arrangements
for the supply of safe food. To design effective coordination arrangements requires to cope with
uncertainty (Mènard, 2005). Information asymmetries exacerbates the influence of uncertainty
(Williamson, 1991).
In sum, on the one hand effective food safety provision systems (Haccp, Certification, Traceability,
Certification etc) are based upon or provide organizational solutions of both coordination and
information issues; on the other hand, technological and behavioural uncertainty require the agents to
allocate resources to food safety systems intended to channel information along the chain and to favour
the coordination among the agents (Hammaudi et al., 2009; Hirschauer, Zwoll, 2008; Hobbs, 2004;
Mènard, Valceschini, 2005; Dosman et al., 2001; Unnevher, Jenson, 1999). We then consider the
investments in food safety systems both as economic instruments to implement safety strategy and as
elements related to organizational choices. In the following we elaborate on these points by focusing on
the allocation of decision rights as critical step in building up effective safety provision systems.
2.3
Public intervention and allocation of decision rights
The necessity of copying with risks emerging in food chain determined the building up of complex
regulatory frameworks (Majone, 2010; Szajkowska, 2009). During the recent decades an intensive
change of the institutional framework has been implemented at both national and international level in
order to enhance and to ensure the degree of safety of the food products (Fulponi, 2006; Lupien, 2005;
Yapp, Fairman, 2006; Garcia-Martinez et al., 2007; Henson, Holt, 2000). The agri-food chain coordination
patterns progressively change under the inducements of the co-regulation approaches (Garcia-Martinez
et al., 2007) as well as the increasing influence of the food standards’ adoption (Swinnen,
Vandermoortele, 2009; Hammoudi et al., 2009; Trienekes, Zuurbider, 2008). The implementation of
safety oriented activities is associated with monitoring and controlling while signalling to consumers and
230
Gaetano Martino and Miroslava Bavorovà
chain partners the degree of safety of the products delivered is a critical strategic tool (Elbash, Riggs,
2003; Golan et al., 2001). Beyond the compliance with the law, agents have identified specific objectives
that concern private standards (Hobbs et al., 2002; Trail, Koening, 2010; Hammoudi et al., 2009;
Henson, Reardon, 2006; Trienekens, Zuurbier, 2008), complex information management systems
(Charlier, Valceschini, 2008; Heyder et al., 2012) and signalling devices (Hatanaka et al., 2005; Golan,
2003; Konefal, Hatanaka, 2011).
The alignment of the behaviour of the agents, is a critical an instrument to cope with technological and
behavioural uncertainty (Hirschauer, Mussoff, 2006). Our approach elaborates on the idea that the
allocation of the decision rights is the tool to sustain the achievements of safety requisites. Theory
states that in order to cope with uncertainty the parties negotiate ex ante the allocation of the critical
decision rights to the party who is expected to maximize the total surplus (Gibbons, 2005; Gibbns et al.
2013). Although the parties could not anticipate at the time of the contract outset all the future specific
necessities which may rise due to inherent uncertainty of food safety, they may decide how to face
these necessities by allocating the critical decision rights at the time of the negotiation of the
governance structure. Drawing from Gibbons (2005) we contend that the coordination pattern among
two parties in the chain may follow the following timing:
.
Governance structure
negotiation, with
allocation of decision
rights about the food
safety strategies
implementation
t1
Production process
carrying out (ex
ante action chosen)
Emerging of the
unforeseen food
safety threats
(interim signals
observed)
t2
t3
Implementation
of the food
safety strategy
(ex post
decision taken)
t4
Pay-off
received
t5
Figure 1. Allocation of decision rights about food safety private strategy and timing of implementation
The figure 1 indicates that the choice of the governance mode allows the parties to coordinate
themselves to the purpose of safety provision. The allocation of the decision rights is aimed at allowing
the parties to achieve the largest surplus, provided the uncertainty influence (Gibbons, 2005;
Williamson, 1991). We contend that the relevant rights set includes also the right to decide the
investments required to design and implement the investments needed to set up the safety provision
systems.
Many factors inducing the adoption of food safety standards can have an effect on the allocation of the
decision rights. In general, the compliance with law (Henson, Holt, 2000) limits the freedom of contract
of the parties and modifies their degree of freedom in the decision making process. The external
pressure caused by the chain partners or final consumers (Trienekens, Zuurbider, 2008) has a similar
impact. The size of the firm can influence the adoption of standards (Trienekens, Zuurbider, 2008) and
can interfere on the allocation of the decision rights because of its relation with the capability of the
firm to implement safety system (Yapp, Fairman, 2006). These factor interact with the internal
motivation of the firm, the objective to strengthen the market position (Zaiber, Bredhal, 1997), the
search for a premium price (Zhou et al., 2011) and for scale economies (Trienekens, Zuurbider, 2008, p.
120), and the reduction of the transaction costs (Henson, Northern, 1998; Loader, Hobbs, 1999).
Public intervention and private strategies set up a complex network of rules and incentives aimed at
achieving an enhanced degree of food safety (Garcia Martinez et al., 2007). Food safety rules have
influence upon the decision rights concerning the process implementation, the enforcement, and the
monitoring and controlling activities as well as the design of entire food safety systems. The parties to a
transaction may agree upon a given allocation of decision rights in order to achieve the higher efficiency
possible in coping with uncertainty. Nonetheless, based on the comparison of benefits and costs of
effective safety strategies (Antle, 1999; Garcia Martinez et al., 2007), the policy intervention may
231
Gaetano Martino and Miroslava Bavorovà
delimitate the right to decide the allocation of decision rights and may also force the parties to a adopt a
given allocation.
2.4
Food safety investments drivers
To the purposes of our analysis, we distinguish the right to decide the allocation of the decision right to
invest from the decision right to invest. If the public regulation prohibits to carry out a given productive
operation, then none of the parties to a transaction can carry out that operation: none of the party will
invest to the purpose of that operation. If the public regulation constrains a party to carry out the given
operation, then the party has to invest and none can decide how to allocate the decision right to carry
out the operation. Therefore it seems that public prohibitions and prescriptions share a common
general trait, actually both of them deprive the parties of the right to decide the allocation of decision
rights related to the objective of the public intervention.
In terms of decision rights, then, the first effect of the public intervention we consider is to deprive or
not the private agents to decide the allocation of decision rights. The figure 2 illustrates the investments
drivers we identified.
deprive
Allocation of decision
rights by law
(regardless to whom make
the investments)
driver: LAW
Legislation
driver: AUTONOMY
not deprive
Allocation of decision
rights by freedom of
contract
driver: PARTNER DIRECTIONS
Figure 2. Identification of the investments drivers
In the first case, the critical decision could be made by public officers or by private agents but strictly
according to public prescriptions or prohibitions. As a consequence the investment decision would be
made by the force of the law. This is the field of compliance with the legislation. The second case is that
grounded upon the freedom of contract: the parties will behave according to the model depicted in
Figure 1. On the other hand, buyers and consumers expectations could induce companies to invest in
order to ensure and to enhance the degree of safety of the products. In other words, if the law does not
deprive the parties of the right to decide the allocation of the decision right to invest, then free
decisions can be made. The parties have thus the freedom to make investments to the purposes of
safety performance and surplus maximization. The party to a transaction could decide to maintain the
decision right to invest as she expect to maximize the total surplus of the transaction. The autonomy –
that is the capacity and willingness to act by herself - is thus an additional investments driver often
crucial in the implementation of marketing plan based on safety and quality (Martino, Perugini, 2006,
Fulponi, 2006). Moreover, to deal with the coordination and information food safety management issue,
a party may decide to allocate to the counterparty the right to invest, in such a case the investment will
be made under the directions of the partners which is then the third driver we identify.
If the decision about the allocation of the decision right to invest can be freely made according to the
complete freedom of the private agents, the parties will choose the efficient allocation of the decision
rights to invest (Gibbons, 2005). Therefore, under the point of view of a transaction party, we
distinguish two cases: a) the decision rights is fully exerted according to the liberty of the transaction
party, we label “Autonomy” this case; b) the decision right is allocated to the transaction counterparty
(“Partner directions”). We operationalize this conceptual approach by two steps (par. 2.3): we firstly
232
Gaetano Martino and Miroslava Bavorovà
introduce a selection hypothesis intended to capture the influence of the policy interventions on the
decision patterns and then we identify the types of investments drivers.
3
Empirical study
According to Loader and Hobbs (1999) food safety investments are expected to be made in all the
critical areas of firm activities. We considered a wide definition of food safety system, namely we
consider all the system based on the qualification of the production processes or the product paying
explicit attention to safety.
We consider five basic organizational systems that have been developed to achieve food safety and food
quality objectives: Haccp system, which provides the basic possibilities to implement the right
technology; Certification, which integrates the search for signalling objectives and the organizational
innovation (Unnevehr and Jenson, 1999; Crespi & Marette, 2001); Geographic Indications, which
require the producers on the supply side to comply with specific rules and, on the demand side, are able
to channel adequate information toward consumers (Louriero, Umberger, 2007); Brand, which are used
to signal of quality and safety characteristics even though consumers seem to prefer public labelling
(Roosen et al., 2003); Traceability which facilitates the management of supply chain by the possibility of
identifying liabilities by enhancing the efficiency of control activities (Heyder et al., 2012; Starbird,
Amanor-Boadu, 2006; Hobbs et al., 2005; Hobbs, 2004) and supporting trasparency (Beulens et al.
2005).
3.1
Method of analysis
How does the relationship between the allocation of the decision right to invest work in the context of a
strong legislation pressure? Consider the case in which paradoxically any legislation existed on food
safety, the parties to a transaction would have the convenience to decide the allocation of the decision
right to invest in order to cope with uncertainty and coordinate themselves. Of course we cannot
observe the allocation of decision rights impact in the case of absence of legislation, because it is not
real. We only can observe farms and companies which are under the legislation pressure as the safety is
a pre-requisite of the food. Therefore, observing the real farms and companies we may not be able to
capture completely the relation between the allocation of the decision rights and the investment
decision concerning the necessity to cope with uncertainty in food safety context. In other words, we
are observing a “decision making space” in which both law and free willingness could operate as
determinants of the allocation of decision right to invest. Asking agents to declare what are the drivers
of the investments they made, we are sampling decisions in that “decision making space” and the
decisions sampled may be not representative, if the logical possibility exists that the decision to allocate
the decision right is made regardless to law (this is for example the case of the supply of meat-food for
kids). Actually the investment decision right could have been allocated without law pressure, but as we
can only observe decision made in law pressure context, it makes sense to make the hypothesis of
selection.
Furthermore, the food safety investments may span from the simply change of the way to carry out an
unique productive operation to the set up of complex traceability or certification systems. Asking agents
to declare if they have invested exploring this very large field would provide answers not fully
comparable. A focus on system is needed, in order to capture comparable behaviors. Unfortunately, the
system view, includes several possible motivation including the competing quality and safety aims.
Both the two reasons illustrated motivates a selection bias. In order to test for the selection hypothesis
discussed above, the method of data analysis is based on the estimation of a bivariate probit model with
sample selection (Greene, 2008). The model includes a selection equation and an outcome equation.
The selection equation accounts for the decision based on the utility of undertaking the change under
the inducements of the legislation pressure. The change process indicates that the farm/company of the
respondent reacted to the food safety legislation pressure. In this context, decisions to invest could have
been made which are of the interest in the present study. In other words,
233
Gaetano Martino and Miroslava Bavorovà
(1)
where:
Y1* = α 1 X 1 + ε 1
Y1* is a latent variable which refers to the utility to undertake the change, mainly related to the
compliance with the law (Hirschauer, Zwoll, 2011);
α is a vector of unknown parameters;
X 1 is a a vector of exogenous variables;
ε 1 is the error terms.
The outcome equation expresses the decision based on the utility of making the investments, having
undertaken the change under the inducements of the general law pressure:
(2)
where:
Y2* = β 2 X 2 + ε 2
Y2* is a latent variable which refers to the utility to undertake the change;
β is a vector of unknown parameters;
X 2 is a vector of exogenous variables;
2 is the error terms.
The decision patterns summarized by the equation (1) and (2) can be depicted as follows (see also
Signorino, 2002):
Food safety law
inducements
Y1* = 1
Y1* = 0
No change
Change
Y2* = 1
Decision based on the
latent variable
U2*
(outcome equation)
Decision based on the
latent variable
U1*
(Selection equation)
Y2* = 0
No food safety
investments
Food safety
investments
Figure 3. Investments decision pattern
Of course, we only can observe the decisions made when the latent variables are larger than 0.
Our approach to empirical analysis focuses on how the three drivers considered influence the
probability to invest. Each of the drivers considered may have the same (positive, negative) or a
different impact on that probability for all the types of investments taken into account. If the impacts on
the three types of investments have the same (different) sign, then we conclude that inducements of
each driver (Law, Autonomy, Partner directions) converge (diverge) toward the same effect, increasing
(decreasing) of the probability to invest. Our method of data analysis focuses on association. The
convergence (divergence) in terms of types of investments regards how the impact of each driver is
234
Gaetano Martino and Miroslava Bavorovà
associated to each type of investments. The convergence (divergence) in terms of drivers concerns with
how for each investments the drivers associate themselves. The types of association of the drivers, with
respect to each investments highlights instead how public interventions and private strategy combine
themselves.
3.2
Data
The empirical analysis was carried out gathering data by using the data base built on in 2005-2006 by
through a postal questionnaire submitted to 2036 Italian companies. The postal address were achieved
from Posteitaliane – the company managing mail services at national level – and the selection of the
companies was carried out by the unique criterion of “Field of activity”. The companies selected were
active in the field of animal products supply and were engaged in various stages of food chains (i.e.,
agricultural, processing and just trading activities).
The Italian meat sector includes several branches of activities spanning from farm stages production to
distribution activities. The sector is based upon a variety of organizational forms strongly influenced by
the quality and safety policies and a large diffusion of certified products. The main branches of activities
are the bovine, the pork and the poultry (see Table 1 for details). The policy intervention strongly
influenced the organization of the sector. Changes occurred in order to face the BSE crisis and the avian
flu. Nevertheless, the sector is characterize by the prevalence of vertical integration in poultry industry
and by the diffusion of contractual relationships (among farmers and processors, and processors and
retailers) in bovine and pork industry. These variety motivates a different approach in dealing with
safety strategies.
The instrument used in our inquiry includes three sections: a) general information about the company,
including the date of establishing, the size and the field of activities (production, trade); b) the
relationships with other enterprises in the chains, the section focus of the type of contract (verbal,
written, brief term, long terms) and related decision (procurement, selling, duration), the information
related are not presented here, but are part of a further investigation; c) the activities undertaken in the
field of food safety: the information concern with the typo of systems implemented (Haccp,
Certification, Brand, Geographical Indication, Traceability, none) and the investments made in order to
support the system built on (physical resources, human resources, additional costs); further information
concern with: the sources of information on safety, the implementation of specific hygiene practices
and the internal safety
235
Gaetano Martino and Miroslava Bavorovà
Table 1.
Some characteristics of the Ialian meat sector
u.m.
2008
2009
2010
N. of farms
(000)
93
93
93
Head slaughtered
(000)
1869
1882
1890
Meat supply
(Mil Euros)
1057
1049
1069
Sales
(Mil Euros)
5900
5900
5900
Import
(Mil Euros)
3122
3138
3336
N. of farms
(000)
-
-
Head slaughtered
(000)
-
-
Meat supply
(Mil Euros)
1606
1628
1673
Sales
(Mil Euros)
7578
7601
7928
Import
(Mil Euros)
1839
1765
1972
N. of farms
(000)
-
-
Head slaughtered
(000)
-
-
Meat supply
(Mil Euros)
1237
1247
1319
Sales
(Mil Euros)
5300
5320
5300
Import
(Mil Euros)
146
131
163
Bovine
Pork
26
-
Poultry
11117
-
Source: Ismea (2012)
3.3
Variables
There are many studies considering different aspects of the organisational systems of food safety
management in various settings. Karaman et al. (2012) investigated the managers’ opinions about Haccp
in Turkish dairy. The additional costs and the lack of adequate physical conditions were ranked at the
first position among the barriers limiting the diffusion of Haccp system. Economic incentives and the
necessity to comply with the law are identified as the main goals to be achieved through the
implementation of Haccp. Wilckok et al. (2011) propose similar motivation for the adoption of food
safety systems, including Haccp. According to the received literature (Acemoglu,1996; Lepak and Snell,
2002) the human resources are recognized as the main requirement for the implementation of an
effective food safety system (Wilcock et al., 2011, pp. 29 ff.). By an extensive analysis Herath and
Henson (2010) found out that the main obstacle to diffusion of Haccp would be the financial constraints
while confirming that the consumers’ requests act as the great inducement to adopt. Notably they
pointed out that the size of the company appears to be not influent.
Collins and Burt (2006) show that brand strategy requires both the parties to a dyad relationship to
make specific investments (but they do not emphasize the allocation of decision rights). Quetier et al.
236
Gaetano Martino and Miroslava Bavorovà
(2005) found out that typical cheese producers modified the land use and the genotypes improvements
strategies in order to enhance their compliance with Geographical Indication production rules. Heyder
et al. (2012) provide a comprehensive analysis of the traceability implementing and management in the
lens of the technology acceptance model. Their results showed that the costs caused by the
management of the traceability systems negatively influence the choice to adopt them, while the
intention to invest has a positive role in the diffusion of these systems. Further scholars underlined the
necessity to face increased costs caused by the adoption of the food safety systems (Seggerson,1999;
Henson, Reordan, 2001; Antle; 2000). In this context, although the investments in food safety may
consist in material resources, human resources and in organisational activities, scholars recognize that
human resources, staff skills and training and information technologies are the most prominent
resources sustaining food safety systems. This circumstance implies that human resources and
additional costs are expected to be more diffused investments made in order to support food safety
strategies. Nevertheless, physical resources appear to maintain a role, even though associated to the
technological and management changes (Herat et al. 2011; Heyder et al., 2012).
To the purpose of the empirical analysis we therefore considered three types of investment mentioned
for each system: a) physical resources; b) human resources; c) additional costs of the internal
organizational activities. The variables utilized in the analysis are illustrated in Table 2
The code (0,1) indicates as usual the presence/absence of the variable. Thus in the case of investments
the value 1 indicates that the respondents declared she invested. In the case of the driver, the value 1
indicates that the respondent recognized the influence of that driver.
The Beliefs variables capture the influence upon behaviours (decision to invest) that accounts for the
general views of the respondents about the food safety strategies. According to literature, we identified
three prominent beliefs: the compliance with law (Loader, Hobbs, 1999; Henson, Holt, 2000; Antle,
2000; Trienekens, Zuurbider, 2008); the expectations about the profitability in terms of number of
clients and sales (Trienekens, Zuurbider, 2008; Segerson, 1999; Gorris, 2005; Zhou et al., 2012); and of
premium price for the certainty of the safety degree (Loader, Hobs, 1999; Trienekens, Zuurbider, 2008;
Fares, Rouviere, 2010).
237
Gaetano Martino and Miroslava Bavorovà
Table 2.
Variables description and coding
Variable
Investments
Physical Resources (Haccp, Certification, Geographical Indications, Private
Brands, Traceability)
Human Resources (Haccp, Certification, Geographical Indications, Private
Brands, Traceability)
Additional Costs (Haccp, Certification, Geographical Indications, Private
Brands, Traceability)
Investment Drivers
Law
Autonomy
Partner directions
Beliefs
Symbol
Code
PR
(Haccp,
Cert,
Gi,
Brand,
Trace)
HU
(Haccp,
Cert,
Gi,
Brand,
Trace)
CO
(Haccp,
Cert,
Gi,
Brand,
Trace)
0, 1
Law
Auton
Partndir
0, 1
0, 1
0,1
Law_duty
I completely disagree
I disagree
I do not know
I agree
I completely disagree
I completely disagree
I disagree
I do not know
I agree
I completely disagree
I completely disagree
I disagree
I do not know
I agree
I completely disagree
To ensure food safety is a law duty
To ensure food safety increases the number of clients and the sales
Custom
Price
To ensure food safety increases the prices of the products
Sources of information
Technicians
Public Health officials
Advertsing
Other entrepreneurs
Control variables
Number of high level managers, as index of the capability to cope with
technological uncertainty;
0,1
Tech
Asl
Publ
Enterpr
0, 1
0, 1
0, 1
0, 1
Ndir
Number
Year of experience of the top manager, as index of the capability to cope
with technological uncertainty;
Exper
Volume of sales as an index of the size of the firm;
Sales
Dichotomous variable, indicating the stage of activity of the firm
(production = 1; distribution = 0).
Prod
238
0, 1
-2
-1
0
1
2
-2
-1
0
1
2
-2
-1
0
1
2
< 5 years
6 – 15 years
16-25 years
< 25 years
0-100.000 Eur/year
101.000-500.000 Eur/year
501.000-1.000.000 Eur/year
1001.000-5.000.000 Eur/year
more than 5.000.000 Eur/year
0, 1
Gaetano Martino and Miroslava Bavorovà
Each source of information has a specific effect. Technicians are here intended to be associated with
the chain relationships (the connection between poultry companies and farmers under contract, for
example, is normally guaranteed by the company’s technicians network), therefore we expect that this
variable strengthen the role of Partnreq in explaining the investments decisions. Analogously, we expect
that Asl is associated with Law, being the public Health related to legislation. Adv is here intended as a
free source of information, vehiculating a zero cost information. With Other entrepreneur we thus
capture the horizontal exchange of information, mainly channelled in the networks relationships (Omta
et al., 2001). The information considered here concerns with the technology and the related risks. A
positive effect of these variables would indicate that the source influences the probability to invest.
With Control variables we account for variable which may be supposed to influence the decision to
invest, but that are not related to the decision to allocate the decision right to invest. Shaosheng et al.
(2008), Yapp and Fairman (2006), Fulponi (2006) emphasize the importance of the experience of the
entrepreneurs and managers to the end of adopting food safety systems. Both Ndir and Experience are
intended to account for the capability – based upon tacit knowledge - to cope with technological
uncertainty and then to invest.
Scholars underlines the role of the size of the business in adopting food safety systems. Loader and
Hobbs (1999) argue that the legislation can charge small firm of larger costs because of the lack of
economies of scale. Trienekens and Zuurbider (2008) underlines the difficulties of small firms to comply.
Scale is also invoked to account for different impact and technological risks and well as difference in the
class of operations. These differences would be so marked to require different approaches at the
various scale of business (Delind and Howard, 2008). We therefore introduced the variable Sales in
order to account for the influence of scale. The variable Prod, finally, is considered to account for the
potentially different behaviour in units specialized in trade with respect to those engaged in production
or also in production.
3.4
Empirical results
177 questionnaires were filled and returned back (response rate: 8.89%). Among these questionnaires,
117 provided the data used in the present study. The remaining were incomplete and lacking some of
the variables needed. The Table 3 illustrates the characteristics of the sample data.
239
Gaetano Martino and Miroslava Bavorovà
Table 3.
General characteristics of the sample
Variables
Managers (n. units)
Technicians (n. units)
Employers (n. units)
Skilled workers (n. units)
Generic workers (n. units)
409
818
77
1988
9923
Age of top manager (years)
≤ 30
31-50
> 50
9
81
89
Elementary school
Junior High School
High School
University Degree
20
52
93
13
Education of the top manager
Job experience of the top manager (years)
≤5
6-15
16-25
>25
9
21
49
99
Production
Trade
Production and trade
47
97
33
Branch of activity (n.units)
Source: the Authors
The sample is characterized by a small presence of skilled workers and technicians. The age of the top
managers is of medium or high level. There is a really small percentage of managers with an University
degree. This fact could appear to be compensated by the prevalence of large work experience. The
26.6% of the units investigated is specialized in production, the 18.6% in production and trade, whereas
the 54% is specialized in trading activities.
In the following we briefly illustrates and discuss the results concerning the selection hypothesis (sample
selection bivariate probit models).
Table 4 summarizes distribution of the drivers resulting from the questionnaires. The legislation
pressure is the most influential drivers in Haccp and Traceability, but it maintains an important role also
in Certification and Geographical Indications. Autonomy and Partners directions are prominent in
Certification, Geographical indications and Brand, with an evident role for the allocation of decision
rights to the transaction counterparties.
240
Gaetano Martino and Miroslava Bavorovà
Table 4.
Distribution of drivers by safety systems
System
Law
Autonomy
Partner
directions
Haccp
72.7
25.0
2.3
Certification
22.5
69.0
8.5
Geographical Indications
27.3
63.6
9.1
Brand
14.0
76.7
9.3
Trace
57.4
39.0
3.7
Source: the Authors
241
Gaetano Martino and Miroslava Bavorovà
Table 5 (Part I).
Bivariate sample election models
HACCP
PR_Haccp
HR_Haccp
Certification
CO_Haccp
PR_Cert
HR_Cert
Geographical Indications
CO_Cert
HR_Gi
CO_Gi
Private Brand
HR_Brand
Traceability
CO_Brand
PR_Trace
HR_Trace
CO_Trace
MAIN
Law_Haccp
1.037***
0.727***
0.276
Auton_Haccp
0.211
0.0451
-0.202
Partndir_Haccp
8.117
-8.669
10.55
Law_Cert
Auton_Cert
Partndir_Cert
12.184***
-6.220***
1.102**
6.627***
0.833***
0.564**
6.6753***
0.613***
1.046*
Law_Gi
-4.169
7.418
Auton_GI
0.511
0.693*
-
-3.785
Partndir_Gi
Law_Brand
Auton_Brand
Partndir_Brand
-1.914***
0.666
0.48
0.354**
-2.176**
0.615
Law_Trace
*
0.786*
0.437***
-3.745
Auton_Trace
0.163
0.442***
0.0542
Partndir_Trace
8.460
-4915***
-4.294
_cons
0.634***
-5.822***
-1.518***
-1.285**
0.962
Change
Law
Custom
-0.311
0.241
-0.0631
0.191
0.0703
0.217
-0.1083627
-0.208
-0.143
-0.274
-0.0892
-0.214
0.0558
-0.315*
-0.136
-0.452***
-0.232
-0.171
-0.184
-0.3853***
-0.315*
-0.352***
-0.427**
* -0.425**
-0.174
-0.392**
242
Gaetano Martino and Miroslava Bavorovà
Table 5 (part II).
Bivariate sample election models
PR_Haccp
HACCP
Certification
HR_Haccp CO_Haccp PR_Cert
HR_Cert
Geographical
Indications
CO_Cert
HR_Gi
Private Brand
CO_Gi
Traceability
HR_Brand CO_Brand PR_Trace
HR_Trace
CO_Trace
Price
0.266*
0.0902
0.302**
0.214*
0.244
0.197 0.26117**
0.283*
0.276***
0.380**
0.222
0.102
0.248*
Tech
0.0771
0.251
-0.0694
0.339
0.452
0.563 0.1593706
0.0958
0.0604
0.024
-0.0646
-0.111
0.367
Asl
0.709
0.992
0.37
1.049**
1.303***
1.050 0.3638364
0.756
0.298
0.475
0.494
0.641*
0.896
PublAdv
0.0868
0.364*
0.0932
0.134
0.0376
-0.0759 0.1298488
0.0162
0.24
0.0877
-0.0163
0.183
0.218
Enterpr
0.349
0.423
0.676*
0.348
0.372
0.404
0.159
0.482
0.618*
0.661***
0.649*
-0.0107 -0.00473 -0.00281 -0.00878
0.0000051 -1.51E-06 -2.71E-07 -7.32E-07
-0.0125*
0.672* 0.2991006
-0.00539 0.01106**
-0.0094
-0.0108*
-0.0104
-0.0052
-0.009***
-0.0057
Ndir
Sales
Exper
0.000328
_cons
0.00744
-0.00374
-2.398*
N
112
2
Wald
2
112
19.03 5.13+e12
-5.54E-06 -2.38E-06
-4.33E-06 -5.55E-06
0.00933 0.0011764 -0.00415
-10.24 -5.22E-07 -2.72E-06
0.0131**
0.0152
-2.324*
-2.568**
-2.554*
112
112
112
112
112
112
112
112
112
112
19.97
1.97
3.6
2.39
199.39
6.82
112860.46
0.8
0.0000
0.0020
0.3700
0.3000
0.4900
0.0000
0.0800
0.0000
0.8500
112
1989.77
.
.
1.6+e11
0.00115
0.00267
-0.00292
-7.39-06** -2.74E-06
-0.0026
0.098
-1.840
Prob >
0.0003
0.0000
0.0000
-0.793
-1.000
-1.000
-1.000
1.000
1.000
0.935
-0.939
-0.883
-1.000
1.000
-1.000
-0.696
4.17
0.19
5.42
165.55
6.67
40.53
106.43
29.34
10.67
35.46
8.55
7.86
0.5
0.0410
0.6700
* p<0.01, ** * p<0.001
0.0200
0.0000
0.0098
0.0000
0.0000
0.0000
0.0000
0.0000
0.0035
0.0050
0.4770
2
2
Prob >
* p<0.05, *
243
Gaetano Martino and Miroslava Bavorovà
The Table 5 illustrate the estimates for the sample selection bivariate probit model.
The selection hypothesis holds for all the systems considered except than in the case of investment in
Human resources for Haccp (HR_Haccp) and in Additional costs for traceability (CO_Trace). In the
following we provide details about the statistical results paying attention to the selection hypothesis,
the statistical significance of the coefficients estimated.
Haccp
The driver Law_Haccp is explains the investments decisions both for Physical and Human Resources.
Among the beliefs variables, only the duty to comply with the law (Law) and the expectations about the
increase of clients and sales (Custom) have an explaining capacity in the case of CO_Haccp, while only
Adv is significant in the case of HR_Haccp. Enterpr explains the investments in Additional Costs
emphasizing the importance of horizontal relationships. The influence of legislation is evident and it is
associated with the expectations having a clear private economic sense. This results reflects the
literature achievements (Trienekens, Zuurbider, 2008; Loader, Hobbs, 1999; Gorris; 2005; Lupien, 2005).
Certification
All the drivers considered contributes to explain the investments decisions. The change equation
estimates provide a more articulated picture. Price expectations, health authority information (Asl) and
the experience of the managers (Exper) are significant in the case of the investments in Physical
resources. Asl and Ndir are influential in the
case of the Human resources, but only the coefficient of Enterpr is statistically significant in the case of
the investments in Additional Costs.
Geographical Indications
Only the coefficient of Auton-Gi is statistically significant for the Geographical indications system in the
case of investments in Additional Costs. Among the beliefs considered Law and Price have significant
coefficient for the investment in Human Resources and Additional Costs for Geographical indications.
The control variable Ndir is significant in the model for HR_Gi.
Brand
While Law and Partners directions have significant coefficients in the case of HR_Brand, the driver
Autonomy is significant in the case of CO_brand. The belief Custom and Price are influential in both the
two models, but only the control variable Ndir has a significant coefficient and only for HR_Brand.
Traceability
The driver is significant in the case of the Physical resources, while all the three drivers are significant in
the case of the Human resources investments. For the change equation, the expectation custom and
the information from the other entrepreneurs (Entepr) have significant coefficient for Physical
resources, Human resources and Additional Costs. Among the control variables Ndir and Sales have
significant coefficient in the case of Human resources investments.
The results delineate a complex picture of the influence of the allocation of the decision right to invest.
Certification is a clear case of common influence of the three drivers, in such a case the public
intervention and the private strategies combine themselves in a convergent manner for physical
resources. In the case of Human resources the legislation pressure has a negative, divergent influence.
This indicates that the presence is directed toward physical resources and additional costs. Although
the Human resources are relevant to safety outcomes, the legislation pressure has a positive influence
because investments are usually idiosyncratic (Williamson, 1985) and this strengthen the coordination
(Martino, Perugini, 2006). Notably Autonomy and partner directions are positive and convergent for all
the three types of investments. The legislation influence is of particular importance in Haccp, the mostly
diffused system (Yapp, Fairman, 2006; Henson, Holt, 2000). The explaining capacity of the Beliefs is
mostly evident in the remaining four systems, in which the free choice of the partion is normally more
pronounced. The explaining contribution of the source of information is not evident. Notably the
horizontal relationships are important in the case of Traceability, which rests on the contact among the
244
Gaetano Martino and Miroslava Bavorovà
chain stages. The Ndir confirms the importance of knowledge to design and to implement food safety
strategy. We have to point out that there is not an evidence for the role of size, despite the indications
of literature. In synthesis our results indicates a large explaining capacity of an approach based upon the
analysis of the allocation of the decision right to invest.
After having delineated the patterns of explanation, a natural step is to examine the impact of the
drivers on the decision to invest (Greene, 2008). The Table 6 summarizes the average marginal effects
(AMEs) estimated for the drivers of the outcome equation: the AMEs indicate how change the
probability to invest under the inducement of the driver considered. They are estimated for all the units
of the sample and then the average value is calculated.
245
Gaetano Martino and Miroslava Bavorovà
Table 6.
Sample selection bivariate probit models - Average Marginal Effects by systems
Drive
rs
Certificati
on
HACCP
PR_HACC HR_HACC CO_HACC PR_CER
P
P
P
T
Law
Auto
n
HR_CERT
Gegraphical
Indication
CO_CERT
0.330841 0.258092 0.213173 0.17676 0.148679 0.300714
1***
8***
8
17
2
9***
(2.46)
(16.68)
(1.38)
(1.73)
-(0.02)
(5.73)
0.050485 0.014062
0.26677 0.162783 0.190323
0.054774
9
6
22*
6**
***
(0.39)
(0.10)
(0.40)
(1.13)
(1.94)
(3.34)
Partn 0.203054 0.717861 0.306265
dir
6
7***
4***
(1.51)
-(8.92)
(2.28)
0.143411 0.271460
2***
8***
(18.40)
(3.43)
PR_
HR_GI
GI
CO_GI
-
0.267 0.477906
*
4***
(0,10)
(0.03)
-
0,083 0.238485
***
3
(0.00)
(1.91)
-
0.504545
1
-(0.16)
-
0-375
(0.015
)
246
Traceab
ility
Brand
PR_BR
AND
HR_BR CO_BRAN PR_TRAC HR_TRA CO_TRAC
AND
D
E
CE
E
-
0.490*
**
(0.00)
0.233377 0.224593 0.15057 0.104500
4***
2**
24
8
(0.01)
(2.11)
(0.00)
-(0.68)
-
0.189
(0.12)
0.134996 0.050196 0.14596 0.015767
7***
2
76
7
(0.01)
(0.43)
(0.00)
(0.11)
-
-0.496
0.216565 0.371002 0.68128 0.764594
3***
6***
65
5***
-
(0.00)
(0.01)
(21.31)
(0.00)
-(2.80)
Gaetano Martino and Miroslava Bavorovà
Haccp
In the model regarding the Haccp system the driver Law has a positive impact on the investment on
Physical, Human resources and Additional costs. The probability of investing in physical resources
supporting Haccp increases by 0.339, and the probability of investing in Human resources also increase
but only by 0.254. The increasing is small than in the case of CO_Haccp (0.080). The Partners directions
act as a drivers increasing the probability to invest in Physical resource by 0.552 and by 0.303 the
probability in the case of Additional Costs, and reducing by -0.718 the probability of investing in Human
resources. Therefore we point out that while Law has a similar influence on both physical and human
resources, the Partner direction has a different influence on the investment in Physical resources,
Human resources and Additional costs. The emerging picture indicates that no autonomous decisions
drive the invest in Haccp system.
Certification
All the three drivers have an impact on all the types of investments in the case of the certification
system. The Law increase the probability to invest in physical resources by 0.787 and by 0.301 in
additional costs, but it reduces the probability to invest in the case of Human resource (-0.208). The
impact of Auton on physical resources is positive and smaller than that of law and Partner directions for
Physical resources and additional Costs, but larger for Human resources. The probability to invest in
human resource is reduce by the Law (-0.208) whereas both the Autonomy and Partners directions
increase it. The impact of Law on the investment in additional costs is larger of the autonomous
decisions and about equal to that of the decisions made by the chain partners. Therefore the
certification system involves a complex allocation of the decision rights along the chain. The first reason
for that is the mandatory and voluntary certification schemes co-exist in the sector examined. The can
also be explained by the evidence that certification requires a strict monitoring of the production
process entailing then the combination of autonomous and partners decisions. Furthermore we note
that, while the decisions of parties tend to increase the probabilities of all the types of investments, the
Law does not promote the investment in human resources. This point is relevant because, while it
reflects the policy inducement to increase costs (Henson, Reordan, 2000), it clearly contradicts the
necessity of sustaining safety strategies with adequate skills and human competences (Yapp, Fairman,
2006; FUlponi, 2006; Gorris, 2005).
Geographical indications
The discussion of the case of Geographical indication can just concerns the model for invest in the
Human resource (-0.552) and additional costs investments (0.601). Notably, we see that the driver Law
reduces the probability to invest in Human resources but increases the probability if investing in
additional costs. This would suggest that the legal framework tends to charge specific additional costs
on the participants to the systems, confirming the existing evidence (Belleti et al…). On the other hand
also the Autonomy decision has a similar effect on Additional costs even though it is weaker.
Brand
The probability to invest in Human resources increases under Law inducements but strongly decreases
with Partndir n the case of Brand system, suggesting a prevalence of the legal framework which limits
the importance of Brand opportunistic relations.
Traceability
The AME of Law is 0.235 in the case of traceability system. The allocation of the decision rights to the
transaction counterparty also reduces the probability to invest in additional costs, indicating that the
chain relationships may entail efficient approaches to that safety system.
247
Gaetano Martino and Miroslava Bavorovà
4
Final remarks
The study addressed the question of how much law compliance and economic and organizational goals
determine food safety investments. We focus on inducements to invest due to the necessity to comply
with the law, to the individual free economic convenience and particularly on the allocation of critical
decision rights to the party who is expected to be able to maximize the relationship total surplus. The
decision to allocate the decision rights appear to be able to influence the choice of the investments as
well as the remaining two drivers. The evidence indicates that the decision rights perspective is
meaningful in order to investigate how public and private activities combine themselves in food safety
provision. Furthermore, the role of public regulation (law) is concentrated in terms of food systems and
types of resources. The allocation of decision right to the counterparty is evident, thus there is also a
confirm of this organizational solution, as predicted by theory, This evidence contributes to shed light
on the strength of the coordination devices associated by safety strategies.
The study presents two main limits. First, the association among the drivers entails both substitution
and complementarity among the investments, but our method does not allow for discriminating these
facts. A specific approach should me carried out (REF). The second limits derives from the fact the our
questionnaires did not provide any information about the allocation of decision rights to collective
bodies, which instead pay a role in many of the systems considered.
The knowledge of the pattern of influence may contribute to design public and private policies aimed at
increasing the degree of product safety.
References
Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior and Human
Antle, J., (1999), Benefits and costs of food safety regulation, Food Policy, Volume 24, Issue 6, December
1999, pp. 605–623
Beulens A.J.M., Broens D., Folstar, P. & Hofstede G.J. (2005). Food safety and transparency in food
chains and networks: Relationships and challenges. Food Control, 16, 6, pp.481-486.
Charlier C., Valceschini E., (2008), Coordination for traceability in food chain. A critical appraisal of
Regulation, European Journal of Law and Economics, 25, 1-15
Crespi J.M. & Marette, S. (2001). How Should Food Safety Certification Be Financed? American Journal of
Agricultural Economics, 83, 852-861
DeLind L.B., Howard P.H., (2008), Safe at any scale” Food scares, food regulation, and scared
alternatives, Agriculture and Human Values, 25, 3, 301-317
Dosman, D.M., Adamowicz, W. L. & Hrudey S.E., (2001). Socioeconomic Determinants of Health- and
Food Safety-Related Risk Perceptions. Risk Analysis. 21, 2, 307-318.
Elbasha, E.H., Riggs, T.L. (2003). The effects of information on producer and consumer incentives to
undertake food safety efforts: A theoretical model and policy implications. Agribusiness, 19, 29-42.
Fare, M., Rouviere E., (2010), The implementation mechanisms of voluntary food safety systems, 35, 5,
412-418
Fielding, L, Ellis, L., Clayton, D., Peters A., (2011), An evaluation of process specific information
resources, aimed at hazard analysis, in Small and Medium Enterprises in food manufacturing Food
Control, Volume 22, Issue 8, August 2011, Pages 1171-1177
Fulponi L., (2006), Private voluntary standards in the food system: The perspective of major food
retailers in OECD countries, 31, 1, 1-13
Garcia-Martinez, M., Fearne, A., Caswell, J.A. & Henson, S. (2007). Co-regulation as a possible model for
food safety governance: Opportunities for public–private partnerships. Food Policy, 32, 3, 299-314
Gibbons, R. 2005. “Four formal(izable) theories of the firm?” Journal of Economic Behaviour &
248
Gaetano Martino and Miroslava Bavorovà
Organization 58 (2): 200-45.
Gibbons, R., Matouscheck, N., Roberts J., (2013), Decisions in organizations, in Gibbon R., Roberts, J.,
(eds.), Handbook of organizational economics. Edited by Robert Gibbons and J. Roberts. Princeton:
Princeton University Press, pp. 373-430.
Golan, E., Kuchler, F., Mitchell, L., Green, C. & Jessup, A. (2001). Economics of Food Labelling. Journal of
Consumer Policy, 24: 117-184.
Goldin C. Katz L.F., (1996), Technology, Skills and the Wage Structure: Insights from the Past, America
Economic Review, vol. 86, 2, pp. 252-257
Grandori A., Furlani S., (2008) Chemistry of Organization: Combinatory Analysis and Design,
Organization Studies, 29, 3, 459-485
Greene, William H. “Econometric Analysis” fifth edition, 2003, Prentice Hall, Upper Saddle River NJ
Hammoudi, A., Hoffman, R. & Surry, Y. (2009). Food safety standards and agri-food supply chains: an
introductory overview. European Review of Agricultural Economics, 36, 468-478.
Hatanaka M., Bain C, Lawrence Busch, 2005, Third-party certification in the global agrifood system, Food
Policy, 30
Henson S,, Hooker N.H., (2001), Private sector management and food safety: public regulation and the
role of private control, International Food and Agribusiness Management Review, 4, pp. 7-17
Henson, S., & Reardon, T. (2005). Private agri-food standards: Implications for food policy and the agrifood system. Food Policy, 30, 3, 241-253.
Herath D., Henson S., (2010), Barriers to HACCP Implementation: Evidence From the Food Processing
Sector in Ontario, Canada, Agribusiness, 26, 2, pp. 265-279
Heyder M., Theuvsen L., Hollmann-Hespos T., (2012), Investments in tracking and tracing systems in
food industry: a PLS analysis, Food Policy, 37: 102-113.
Hirschauer, N., (2006), A game-theoretic approach to behavioral food risks: The case of grain producers,
Food Policy, 32, 2, 247-265
Hirschauer, N., Zwoll, S. (2008). Understanding and managing behavioural risks: the case of malpractice
in poultry production. European Journal of Law and Economics, 26, 1, 27-60.
Hobbs J.E., Von Bailey, D., Dickinson, D.L. & Haghiri, M. (2005). Traceability in the Canadian Red Meat
Sector: Do Consumers Care? Canadian Journal of Agricultural Economics, 53, 1, 47-65
Hobbs, J.E., (20024). Information asymmetry and the role of traceability systems. Agribusiness, 20,4 397415
Hobbs,
J.E.,,
J.E.,Andrew
Fearne,
A.
John
Spriggs,
J.
(2002),
Karaman A. D., Cobanoglu F., Tunalioglu R., Ova G. Barriers and benefits of the implementation of
food management systems among the Turkish dairy industry: a case study, Food Control, 25, 2, pp.
732-739
Holleran E. Bredhal M.E., Zaibet L., 1999, Private incentives adopting food safety and quality assurance,
Food Policy, 24, 669-683
Hutter B.M., Jones C.J., (2007), Form Government to Governance: External influence on business risk
management, Regulation and Governance, 1, pp. 27-45
Ismea, (2013), Rapporto sulle produzioni agroalimentari italiane DOP, IGP, STG, Ismea, Roma
Ismea, Filiera carni e animali, http://www.ismea.it
Lepak D.P., Snell S.A., (2002), Examining Human Resources Architecture: The Relationships among
Human Capital, Employment, and Human Resource Configuration, Journal of Management, 28, 4,
517-543
249
Gaetano Martino and Miroslava Bavorovà
Loader R., Hobbs, J.E., (1999), Strategic response to food legislation, Food Polcy, 26, 6, 685-786
Louriero, M. & Umberger, W.J. (2007). A choice experiment model for beef: What US consumer
responses tell us about relative preferences for food safety, country-of-origin labeling and
traceability. Food Policy, 32, 4, 496-514.
LupienJ.R., (2005), Food Quality and Safety: Traceability and Labeling, Critical Review of Animal Sciences,
45, 2, pp.. 119-123
Martino G., Perugini C., (2006), Hybrid Forms in Food Safety Supply, in Bijman J., Omta O., Trienekes J.,
Wijnands J., Wubben E., (eds.), International Agri-food Chains and Networks: Mangament and
Organizations, Wageningen Academic Publisher, Wageningen, pp. 287-301
Masten S.E., (2000), Transaction Costs Economics and the organization of the agricultural transactions,
Industrial Organization, 9, pp. 173-195
Matthias Heyder, M.,Ludwig Theuvsen, L., Thorsten Hollmann-Hespos T., (2012), Investments in
tracking and tracing systems in the food industry: A PLS analysis Food Policy, Volume 37, Issue 1,
February 2012, Pages 102-113
Mènard, C., & Valceschini E. (2005). New institutions for governing the Agri-food industry. European
Review of Agricultural Economics, 32, 3, 421-440.
Ménard, Claude. 1994. Organizations as coordination devices. Metroeconomica 45 (3): 224-47.
Ménard, Claude. 2004. “The economics of hybrid organizations.” Journal of Institutional and Theoretical
Economics 160 (3): 345-76.
Ménard, Claude. 2005. “A new institutional approach to organization.” Pp. 281-318 in: Handbook of new
institutional economics. Edited by Claude Mènard and M. M. Shirley, 281-318. New York: Springer.
Ménard, Claude. 2006. “Hybrid organization of production and distribution.” Revista de Analisis
Economico 21 (2): 25-41.
Mensah L.D., Julien D., (2011), Implementation of food safety management systems in the UK Food
Control, Volume 22, Issue 8, pp. 1216-1225
Oxley, J. L. (1997). Appropriability hazards and governance in strategic alliances: A transaction cost
approach. Journal of Law, Economics, & Organization, 13: 387-409.
Robertson, F. J., & Gatignon, H. 1998. Technology development mode: a transaction cost
conceptualization. Strategic Management Journal, 19: 515-531.
Roosen, J., Lusk, J.L., & Fox J.F. (2003). Consumer demand for and attitudes toward alternative beef
labeling strategies in France, Germany, and the UK. Agribusiness, 19, 77-90
Starbird S.A. & Amanor-Boadu, V. (2006). Do Inspection and Traceability Provide Incentives for Food
Safety? Journal of Agricultural and Resource Economics, 31, 14-26
Swinnen, J.F.M. & Vandermoortele, T. 2009. Are food safety standards different from other food
standards? A political economy perspective. European Review of Agricultural Economics, 36, 507523.
Tomei F., (2011), Strategie e strumenti di valorizzazione nelle filiere alimentari: la filiera carne,
Econonomia agro-alimentare, 1-2, pp. 203Tompkin R.B. , (2001), Interactions between government and industry food safety activities, Food
Control, Volume 12, Issue 4, June 2001, pp. 203-207
Traill,W. B., Ariane Koenig, A., (2010), Economic assessment of food safety standards: Costs and benefits
of alternative approaches, Food Control, Volume 21, Issue 12, pp.s 1611-1619
Trienekens, J. & Zuurbier, P. (2008). Quality and safety standards in the food industry, developments
and challenges. International Journal of Production Economics, 113, 1, 107-122.
250
Gaetano Martino and Miroslava Bavorovà
Unnevehr L.J., & Jenson, H.H. (1999). The economic implications of using HACCP as a food safety
regulatory standard. Food Policy, 24, 6, 625-635
Unnevehr L.J., & Jenson, H.H. (1999). The economic implications of using HACCP as a food safety
regulatory standard. Food Policy, 24, 6, 625-635
Walker, Gordon., and David Weber. 1984. “A transaction cost approach to make-or-buy decisions.”
Administrative Science Quarterly 29 (3): 373-91.
Wilcock A., Ball B., Fajumo A. (2011), Effective implementation of food safety initiatives: Managers',
food safety coordinators' and production workers' perspectives, Food Control, 22, 1, pp. 27-33
Williamson Oliver. E. 1985. The economic institutions of capitalism. London: The Free Press.
Williamson, Oliver. E. 1991. “Comparative economic organization: The analysis of discrete structural
alternatives.” Administrative Science Quarterly 36 (2): 259-96.
Williamson, Oliver. E., (1999), Public and Private Bureacracies: A Transaction Cost Economics
Perspective, Journal of Law, Economics and Organization, V. 15, 1, pp. 306-343Williamson Oliver. E.
1985. The economic institutions of capitalism. London: The Free Press.
Yapp, C., Fairman, R., (2006), Factors affecting food safety compliance within small and medium-sized
enterprises: implications for regulatory and enforcement strategies Food Control, Volume 17, Issue
1, January 2006, Pages 42-51
251